An interactive 2D intracellular calcium dynamics simulator built with PyQt5 and pyqtgraph. Models the spatiotemporal evolution of calcium concentrations across the cytosol, endoplasmic reticulum (ER), and mitochondria using a reaction-diffusion framework with stochastic IP3 receptor gating.
- Cytosolic calcium: Diffusion, IP3R release, ER leak, SERCA uptake, PMCA extrusion, MCU uptake, and buffering
- ER calcium: Depletion through IP3R and leak channels, refilling via SERCA pumps
- Mitochondrial calcium: Uptake through mitochondrial calcium uniporter (MCU)
- IP3 concentration: Diffusion and degradation dynamics
- IP3R channels organized in clusters with configurable density and channels per cluster
- Open/close probabilities depend on local cytosolic calcium and IP3 concentrations
- Stochastic gating produces realistic calcium puffs and waves
- Reticulated ER network automatically generated within the cell boundary
- Mitochondria distributed throughout the cytoplasm
- Plasma membrane boundary with PMCA pumps
- IP3R clusters positioned on the ER membrane
- Four tabbed views: Cytoplasmic [Ca2+], ER [Ca2+], Mitochondrial [Ca2+], IP3 concentration
- Overlay toggles for cellular structures (ER, mitochondria, plasma membrane) and IP3R channel states
- Real-time pyqtgraph ImageView displays with adjustable color scales
- Start/stop simulation controls
- Default: Standard resting cell parameters
- High Calcium: Elevated cytosolic calcium conditions
- Low Calcium: Reduced calcium levels
- Save and load custom parameter sets through the GUI
The core reaction-diffusion equations:
d[Ca2+]_cyt/dt = D_Ca * nabla^2[Ca2+]_cyt + J_IP3R + J_leak - J_SERCA - J_PMCA - J_MCU - J_buffer
d[Ca2+]_ER/dt = -J_IP3R - J_leak + J_SERCA
d[Ca2+]_mito/dt = J_MCU
d[IP3]/dt = D_IP3 * nabla^2[IP3] - J_degradation
| Parameter | Symbol | Default Value |
|---|---|---|
| Grid size | -- | 200 x 200 |
| Spatial step | dx | 0.1 um |
| Time step | dt | 0.001 s |
| Ca2+ diffusion coeff | D_Ca | 20 um^2/s |
| IP3 diffusion coeff | D_IP3 | 200 um^2/s |
| SERCA pump rate | V_SERCA | 0.4 uM/s |
| SERCA half-max | K_SERCA | 0.2 uM |
| ER leak rate | -- | 0.0002 s^-1 |
| PMCA rate | -- | 0.1 uM/s |
| MCU rate | -- | 0.05 uM/s |
| IP3 degradation rate | -- | 0.1 s^-1 |
| IP3R cluster density | -- | 0.01 |
| IP3R per cluster | -- | 10 |
| IP3R open rate | -- | 0.01 s^-1 |
| IP3R close rate | -- | 10 s^-1 |
| Buffer total | -- | 100 uM |
| Buffer Kd | -- | 0.5 uM |
| Buffer k_on | -- | 100 uM^-1 s^-1 |
| Initial ER [Ca2+] | -- | 500 uM |
| Initial mito [Ca2+] | -- | 0.1 uM |
The 2D diffusion uses a weighted Laplacian kernel:
[[0.05, 0.2, 0.05],
[0.2, -1, 0.2 ],
[0.05, 0.2, 0.05]]
Equilibrium cytosolic calcium is computed analytically from the balance of SERCA uptake and ER leak at steady state.
calcium_simulator/
main.py # Entry point: creates CalciumModel and MainWindow, runs Qt event loop
calcium_model.py # CalciumModel class: reaction-diffusion solver, cell structure, IP3R gating
gui.py # MainWindow class: tabbed visualization, parameter controls, overlays, menus
__init__.py # Package init (re-exports from src subpackage)
default_state.json # Default cell state parameters
high_calcium_state.json
low_calcium_state.json
| Class | File | Description |
|---|---|---|
CalciumModel |
calcium_model.py | Core simulation: grid setup, diffusion, fluxes, IP3R stochastic gating, cell structure |
MainWindow |
gui.py | PyQt5 GUI: four ImageView tabs, parameter dock, overlay controls, cell state menu |
- Python 3.7+
- PyQt5
- pyqtgraph
- NumPy
- SciPy
- scikit-image
pip install PyQt5 pyqtgraph numpy scipy scikit-imagepython main.py- The main window opens with four visualization tabs (Cytoplasm, ER, Mitochondria, IP3)
- Adjust simulation parameters in the control dock on the right
- Click Start to run the simulation; click Stop to pause
- Toggle overlay checkboxes to visualize ER network, mitochondria, plasma membrane, and IP3R states
- Use the Cell States menu to load predefined states or save your current configuration
- Use the File menu to save/load parameter sets as JSON files
- Model parameters: Modify constructor arguments in
calcium_model.pyor adjust via the GUI controls - Cell structure: The
create_cell_structure()method inCalciumModelgenerates ER and mitochondrial geometry - New cell states: Adjust parameters in the GUI and save through the Cell States menu
- Visualization: Modify color scales and overlay rendering in
gui.py
MIT License
Built with AI assistance from Claude (Anthropic).